Total phenolic content prediction in Flos Lonicerae using hyperspectral imaging combined with wavelengths selection methods-Reference-Cited by-同舟云学术

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Total phenolic content prediction in Flos Lonicerae using hyperspectral imaging combined with wavelengths selection methods

Published:2019-08-12 Issue:6 Volume:42 Page:
ISSN:0145-8876
Container-title:Journal of Food Process Engineering
language:en
Short-container-title:J Food Process Eng

Author:

Liu Yunhong¹^ORCID,Wang Qingqing¹,Gao Xiuwei¹,Xie Anguo¹

Affiliation:

1. School of Food and Bio‐engineeringHenan University of Science and Technology Luoyang China

Funder

Henan Natural Science Foundation

Henan Science and Technology Program

Publisher

Wiley

Subject

General Chemical Engineering,Food Science

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jfpe.13224

Reference50 articles.

1. A local pre-processing method for near-infrared spectra, combined with spectral segmentation and standard normal variate transformation

2. Protein content prediction in single wheat kernels using hyperspectral imaging

3. Application of surface enhanced Raman scattering and competitive adaptive reweighted sampling on detecting furfural dissolved in transformer oil

4. Partial Least Squares Regression (PLSR) Applied to NIR and HSI Spectral Data Modeling to Predict Chemical Properties of Fish Muscle

5. Non-destructive and rapid determination of TVB-N content for freshness evaluation of grass carp (Ctenopharyngodon idella) by hyperspectral imaging

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